Titlebook: Natural Language Processing and Chinese Computing; 13th National CCF Co Derek F. Wong,Zhongyu Wei,Muyun Yang Conference proceedings 2025 Th

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書目名稱Natural Language Processing and Chinese Computing影響因子(影響力)




書目名稱Natural Language Processing and Chinese Computing影響因子(影響力)學(xué)科排名




書目名稱Natural Language Processing and Chinese Computing網(wǎng)絡(luò)公開度




書目名稱Natural Language Processing and Chinese Computing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Natural Language Processing and Chinese Computing被引頻次




書目名稱Natural Language Processing and Chinese Computing被引頻次學(xué)科排名




書目名稱Natural Language Processing and Chinese Computing年度引用




書目名稱Natural Language Processing and Chinese Computing年度引用學(xué)科排名




書目名稱Natural Language Processing and Chinese Computing讀者反饋




書目名稱Natural Language Processing and Chinese Computing讀者反饋學(xué)科排名

GLADE

https://doi.org/10.1007/978-981-97-9431-7Information extraction; Machine translation; Discourse, dialogue and pragmatics; Natural language gener

amphibian

MIRTH

ellagic-acid

串通

Learning to?Generate Style-Specific Adapters for?Stylized Dialogue Generatione systems. However, a major challenge to this task is the paucity of supervised data, resulting in suboptimal performance. Although some unsupervised methods have emerged, they tend to handle only a limited range of dialogue styles simultaneously. Retraining becomes necessary when new dialogue style

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裹住

Multi-hop Reading Comprehension Model Based on?Abstract Meaning Representation and?Multi-task Joint ing supporting facts from multiple paragraphs in the document and reasoning to get the answer. But some problems have not been well solved: during the process of extracting the answer, it is often disturbed by the non-real answer (i.e. similar answer) in the document; the lack of a related expressio

蹣跚

Leveraging Large Language Models for?QA Dialogue Dataset Construction and?Analysis in?Public ServiceI) context. Existing datasets often lack the necessary interactive features for effective and efficient interactions, hindering the development of customized and emotionally responsive systems. As public service demands become more diverse and complex in HRI, traditional datasets fail to support hig

ENNUI